Distinct replay signatures for prospective decision-making and memory preservation

The predictive nature of spontaneous brain activity across scales and species

Emerging research suggests the brain operates as a "prediction machine," continuously anticipating sensory, motor, and cognitive outcomes. Central to this capability is the brain's spontaneous activity-ongoing internal processes independent of external stimuli. Neuroimaging and computational studies support that this activity is integral to maintaining and refining mental models of our environment, body, and behaviors, akin to generative models in computation. During rest, spontaneous activity expands the variability of potential representations, enhancing the accuracy and adaptability of these models. When performing tasks, internal models direct brain regions to anticipate sensory and motor states, optimizing performance. This review synthesizes evidence from various species, from C. elegans to humans, highlighting three key aspects of spontaneous brain activity's role in prediction: the similarity between spontaneous and task-related activity, the encoding of behavioral and interoceptive priors, and the high metabolic cost of this activity, underscoring prediction as a fundamental function of brains across species.

Event Segmentation Promotes the Reorganization of Emotional Memory

Event boundaries help structure the content of episodic memories by segmenting continuous experiences into discrete events. Event boundaries may also serve to preserve meaningful information within an event, thereby actively separating important memories from interfering representations imposed by past and future events. Here, we tested the hypothesis that event boundaries organize emotional memory based on changing dynamics as events unfold. We developed a novel threat-reversal learning task whereby participants encoded trial-unique exemplars from two semantic categories across three phases: preconditioning, fear acquisition, and reversal. Shock contingencies were established for one category during acquisition (CS+) and then switched to the other during reversal (CS-). Importantly, reversal was either separated by a perceptible event boundary (Experiment 1) or occurred immediately after acquisition, with no perceptible context shift (Experiment 2). In a surprise recognition memory test the next day, memory performance tracked the learning contingencies from encoding in Experiment 1, such that participants selectively recognized more threat-associated CS+ exemplars from before (retroactive) and during acquisition, but this pattern reversed toward CS- exemplars encoded during reversal. By contrast, participants with continuous encoding-without a boundary between conditioning and reversal-exhibited undifferentiated memory for exemplars from both categories encoded before acquisition and after reversal. Further analyses highlight nuanced effects of event boundaries on reversing conditioned fear, updating mnemonic generalization, and emotional biasing of temporal source memory. These findings suggest that event boundaries provide anchor points to organize memory for distinctly meaningful information, thereby adaptively structuring memory based on the content of our experiences.

Context changes retrieval of prospective outcomes during decision deliberation

Foreseeing the future outcomes is the art of decision-making. Substantial evidence shows that, during choice deliberation, the brain can retrieve prospective decision outcomes. However, decisions are seldom made in a vacuum. Context carries information that can radically affect the outcomes of a choice. Nevertheless, most investigations of retrieval processes examined decisions in isolation, disregarding the context in which they occur. Here, we studied how context shapes prospective outcome retrieval during deliberation. We designed a decision-making task where participants were presented with object-context pairs and made decisions which led to a certain outcome. We show during deliberation, likely outcomes were retrieved in transient patterns of neural activity, as early as 3 s before participants decided. The strength of prospective outcome retrieval explains participants' behavioral efficiency, but only when context affects the decision outcome. Our results suggest context imparts strong constraints on retrieval processes and how neural representations are shaped during decision-making.

Revisiting the role of computational neuroimaging in the era of integrative neuroscience

Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.

Consolidation Enhances Sequential Multistep Anticipation but Diminishes Access to Perceptual Features

Many experiences unfold predictably over time. Memory for these temporal regularities enables anticipation of events multiple steps into the future. Because temporally predictable events repeat over days, weeks, and years, we must maintain-and potentially transform-memories of temporal structure to support adaptive behavior. We explored how individuals build durable models of temporal regularities to guide multistep anticipation. Healthy young adults (Experiment 1: N = 99, age range = 18-40 years; Experiment 2: N = 204, age range = 19-40 years) learned sequences of scene images that were predictable at the category level and contained incidental perceptual details. Individuals then anticipated upcoming scene categories multiple steps into the future, immediately and at a delay. Consolidation increased the efficiency of anticipation, particularly for events further in the future, but diminished access to perceptual features. Further, maintaining a link-based model of the sequence after consolidation improved anticipation accuracy. Consolidation may therefore promote efficient and durable models of temporal structure, thus facilitating anticipation of future events.

Replay-triggered brain-wide activation in humans

The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay.

The role of the human hippocampus in decision-making under uncertainty

The role of the hippocampus in decision-making is beginning to be more understood. Because of its prospective and inferential functions, we hypothesized that it might be required specifically when decisions involve the evaluation of uncertain values. A group of individuals with autoimmune limbic encephalitis-a condition known to focally affect the hippocampus-were tested on how they evaluate reward against uncertainty compared to reward against another key attribute: physical effort. Across four experiments requiring participants to make trade-offs between reward, uncertainty and effort, patients with acute limbic encephalitis demonstrated blunted sensitivity to reward and effort whenever uncertainty was considered, despite demonstrating intact uncertainty sensitivity. By contrast, the valuation of these two attributes (reward and effort) was intact on uncertainty-free tasks. Reduced sensitivity to changes in reward under uncertainty correlated with the severity of hippocampal damage. Together, these findings provide evidence for a context-sensitive role of the hippocampus in value-based decision-making, apparent specifically under conditions of uncertainty.

Reactivation strength during cued recall is modulated by graph distance within cognitive maps

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8 min consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms, with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

Paradoxical replay can protect contextual task representations from destructive interference when experience is unbalanced

Experience replay is a powerful mechanism to learn efficiently from limited experience. Despite several decades of compelling experimental results, the factors that determine which experiences are selected for replay remain unclear. A particular challenge for current theories is that on tasks that feature unbalanced experience, rats paradoxically replay the less-experienced trajectory. To understand why, we simulated a feedforward neural network with two regimes: rich learning (structured representations tailored to task demands) and lazy learning (unstructured, task-agnostic representations). Rich, but not lazy, representations degraded following unbalanced experience, an effect that could be reversed with paradoxical replay. To test if this computational principle can account for the experimental data, we examined the relationship between paradoxical replay and learned task representations in the rat hippocampus. Strikingly, we found a strong association between the richness of learned task representations and the paradoxicality of replay. Taken together, these results suggest that paradoxical replay specifically serves to protect rich representations from the destructive effects of unbalanced experience, and more generally demonstrate a novel interaction between the nature of task representations and the function of replay in artificial and biological systems.

Neural correlates of retrospective memory confidence during face-name associative learning

The ability to accurately assess one's own memory performance during learning is essential for adaptive behavior, but the brain mechanisms underlying this metamemory function are not well understood. We investigated the neural correlates of memory accuracy and retrospective memory confidence in a face-name associative learning task using magnetoencephalography in healthy young adults (n = 32). We found that high retrospective confidence was associated with stronger occipital event-related fields during encoding and widespread event-related fields during retrieval compared to low confidence. On the other hand, memory accuracy was linked to medial temporal activities during both encoding and retrieval, but only in low-confidence trials. A decrease in oscillatory power at alpha/beta bands in the parietal regions during retrieval was associated with higher memory confidence. In addition, representational similarity analysis at the single-trial level revealed distributed but differentiable neural activities associated with memory accuracy and confidence during both encoding and retrieval. In summary, our study unveiled distinct neural activity patterns related to memory confidence and accuracy during associative learning and underscored the crucial role of parietal regions in metamemory.

Distinct encoding and post-encoding representational formats contribute to episodic sequence memory formation

In episodic encoding, an unfolding experience is rapidly transformed into a memory representation that binds separate episodic elements into a memory form to be later recollected. However, it is unclear how brain activity changes over time to accommodate the encoding of incoming information. This study aimed to investigate the dynamics of the representational format that contributed to memory formation of sequential episodes. We combined representational similarity analysis and multivariate decoding approaches on EEG data to compare whether "category-level" or "item-level" representations supported memory formation during the online encoding of a picture triplet sequence and offline, in the period that immediately followed encoding. The findings revealed a gradual integration of category-level representation during the online encoding of the picture sequence and a rapid item-based neural reactivation of the encoded sequence at the episodic offset. However, we found that only memory reinstatement at episodic offset was associated with successful memory retrieval from long-term memory. These results suggest that post-encoding memory reinstatement is crucial for the rapid formation of unique memory for episodes that unfold over time. Overall, the study sheds light on the dynamics of representational format changes that take place during the formation of episodic memories.